Developing ICT-based kiosks for post disaster situational information management using opportunistic networking framework:  As an outcome of our previous project, we have designed and implemented an alternative post -disaster communication infrastructure that may aid the disaster managers and the victims to connect each other even when networking infrastructure is absent/destroyed/damaged; and also an elementary ‘localized’ crisis mapping service prototype on top of the same. In the present proposal, we would like further to extend the same to a larger scale, where they would plan extend the said ‘localized’ crisis mapping service to a full -scale crisis mapping service having the ‘local’ flavor. In addition, more post -disaster services will be identified and implemented on top of the proposed alternative networking infrastructure to aid the disaster managers and the victims. The proposed networking infrastructure use networking resources that have limited networking, storage and computing capacities, and hence judicious use of the same is prior need to achieve decent performance. Finally, on deploying the system in disaster -prone sites and also during real disasters through our so - far obtained links, we may acquire plenty of disaster - related data, which is considered to be very rare in the field of data analytics, mining which we may get many new insights related to disasters. In a nutshell, having completed the proposal, the nation may be armed with a full -scale post -disaster communication alternative with useful post - disaster management services built on it, that may be used by the disaster managers to aid the victims during real crisis hours, and also the planners may collect real - life disaster data through the same system plan better for disaster risk mitigation.

CityProbe: City Scale Pervasive Sensing System: The project proposes a city-scale mobile crowd-sensing framework using portable sensing devices and mobile phone sensors to achieve the following objectives: (a) to measure and analyze (air, sound) pollution levels and to determine road conditions (potholes, bumps) in real-time, (b) to study the inherent causalities between poor road conditions and pollution levels in cities, (c) to present insights derived to city agencies on a dashboard, and as personalized mobile alerts to commuters, (d) to employ opportunistic and participatory sensing models, (e) to explore incentive mechanisms and reputation models to scale participatory crowd-sensing.

IntAirSense: Intelligent Air Pollution Monitoring:   System for Smart Cities using Low-Cost  SensorsDegradation of air quality has been a serious concern in the recent years in cities like Delhi, Kolkata, Durgapur,etc. City population exposed to high concentration of pollutants like CO, NO2, SO2, PM 10, PM 2.5, etc. is suffering from serious health hazards like asthma, bronchitis, emphysema, and possibly cancer. A major approach to deal with the problem is to detect city-wide fine-grained pollutant concentration levels in a continuous basis. Real-time pollution maps should be made available to the public to increase general awareness as well as implement personalized pollution safety measures. Often prediction/forecasting of such concentration might help taking proactive measures. However, precise high-end air quality monitoring involves hugh installation (~15 lakhs) and recurring cost. Major cities could only afford to deploy very few (10 stations Kolkata, 3 stations in Durgapur) pollution sensing stations. Ambient air quality depends on several meteorological factors(temperature, humidity, wind speed/direction, etc.),population density, road traffic, industries, etc. It also changes widely and non-linearly and based on distance as well as time. Hence, presently high-end stations are capable of sampling only a small fraction of large cities. As a result, no real-time pollution maps are available these days. This project aims to develop a cost-effective framework which uses custom built IoT-enabled air pollution sensing boxes (with integrated low-cost sensors). Few of these will be deployed in strategic city-locations and few others will be placed in selected public vehicles to increase coverage as well as enable soft-calibration. We propose to use novel muti-hop calibration techniques to ensure desired accuracy of sensed data as well as machine learning techniques to predict air quality in short term basis. In addition to outdoor, we also aim to use the boxes to monitor indoor air quality and consider designing strategies to minimize pollution exposure in public places like schools.

Post-Disaster Situation Analysis and Resource Management Using Delay-Tolerant Peer-to-Peer Wireless Networks (DISARM)

Rural Development Project Maduli(Amulet), Bankura